Comparison of Lifecorder EX and ActiGraph accelerometers under free-living conditions
Bibliographic record
Abstract
The Kenz Lifecorder EX (LC; Suzuken Co. Ltd., Nagoya, Japan) offers several potentially attractive features for researchers and practitioners compared with accelerometers such as the ActiGraph (AG; ActiGraph Health Services, Fort Walton Beach, Fla.). The purposes of this study were (i) to evaluate the LC's intra-model reliability for outputs of steps and time spent in moderate, vigorous, and combined moderate plus vigorous physical activity (MVPA) and (ii) to compare the same LC vs. AG outputs under free-living conditions. Ten participants (n = 5 males) wore two LCs and one AG accelerometer during all waking hours on one day. Steps were outputted from all monitors. Additionally, two LC and five AG intensity derivations were used to assess time in moderate activity, vigorous activity, and MVPA. Intra-class correlations (ICC) were used to assess intra-model reliability between LCs. Paired t tests and repeated-measures analyses of variance (ANOVAs) were used to assess differences between the two LCs and LC vs. AG outputs of steps and time in various intensity derivations where appropriate. No significant differences were detected between outputs from different LCs (ICCs ranged from 0.95 to 0.99). The LC detected significantly fewer steps vs. AG (mean difference = 1516 steps). All LC vs. AG vigorous-intensity derivations provided similar outputs. Additionally, comparable estimates of MVPA time were produced by one of two LC intensity derivations compared with specific AG cut points established each by Freedson, Hendelman (walking), and Matthews. LC displayed high inter-model reliability. Although the LC detected fewer steps than the AG, the LC detects time in specific PA intensity categories comparable to several existing AG cut points.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".